The main goal of this study is the forecasting of Photovoltaic (PV) power production in Ismailia, Egypt. For the aim of this, a Photovoltaic system was chosen to produce electric power as a clean power. The forecasting process depends on the weather data downloaded from the database of the European Commission's science and knowledge service for the region of Ismailia city, Egypt. The data had been collected for the period of 7 years from 2010 to 2016 and the forecasted period had been chosen to be 12 months for the future prediction. Three Machine Learning algorithms have been developed and tested to forecast the PV power production: Facebook Prophet, Random Forest, and Long Short-Term Memory Networks. It was observed from the results that Facebook Prophet acts more accurate than the others. The preparation procedure of the dataset and the development of the ML models had been built by python programming language to reduce the running time.
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